Structure-activity Relationship Studies on VEGFR2 Tyrosine Kinase Inhibitors for Identification of Potential Natural Anticancer Compounds.

BACKGROUND: Over-expression of Vascular Endothelial Growth Factor Receptors (VEGFRs) leads to the hyperactivation of oncogenes. For inhibition of this hyperactivation, the USA Food Drug Administration (FDA) has approved many drugs that show adverse effects, such as hypertension, hypothyroidism, etc. There is a need to discover potent natural compounds that show minimal side effects. In the present study, we have taken structurally diverse known VEGFR2 inhibitors to develop a Quantitative Structure-Activity Relationship (QSAR) model and used this model to predict the inhibitory activity of natural compounds for VEGFR2. METHODS: The QSAR model was developed through the forward stepwise Multiple Linear Regression (MLR) method. A developed QSAR model was used to predict the inhibitory activity of natural compounds. Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) assessment and molecular docking studies were performed. The binding stability of the natural compounds with VEGFR2 was elucidated through Molecular Dynamics (MD) simulation. RESULTS: The developed QSAR model against VEGFR2 showed the regression coefficient of the training dataset (r2) as 0.81 and the external regression coefficient of the test dataset (r2 test) 0.71. Descriptors, viz., electro-topological state of potential hydrogen bonds (maxHBint2, nHBint6), atom types (minssNH), maximum topological distance matrix (SpMAD_Dt), and 2D autocorrelation (ATSC7v), have been identified. Using this model, 14 natural compounds have been selected that have shown inhibitory activity for VEGFR2, of which six natural compounds have been found to possess a strong binding affinity with VEGFR2. In MD simulation, four complexes have shown binding stability up to 50ns. CONCLUSION: The developed QSAR model has identified 5 conserved activity-inducing physiochemical properties, which have been found to be correlated with the anticancer activity of the nonidentical ligand molecules bound with the VEGFR2 kinase. Lavendustin_A, 3'-O-acetylhamaudol, and arctigenin have been obtained as possible lead natural compounds against the VEGFR2 kinase.

A study on the morbid histopathological changes in COVID-19 patients with or without comorbidities using minimally invasive tissue sampling.

COVID-19 causes morbid pathological changes in different organs including lungs, kidneys, liver, and so on, especially in those who succumb. Though clinical outcomes in those with comorbidities are known to be different from those without-not much is known about the differences at the histopathological level. To compare the morbid histopathological changes in COVID-19 patients between those who were immunocompromised (Gr 1), had a malignancy (Gr 2), or had cardiometabolic conditions (hypertension, diabetes, or coronary artery disease) (Gr 3), postmortem tissue sampling (minimally invasive tissue sampling [MITS]) was done from the lungs, kidney, heart, and liver using a biopsy gun within 2 hours of death. Routine (hematoxylin and eosin) and special staining (acid fast bacilli, silver methanamine, periodic acid schiff) was done besides immunohistochemistry. A total of 100 patients underwent MITS and data of 92 patients were included (immunocompromised: 27, malignancy: 18, cardiometabolic conditions: 71). In lung histopathology, capillary congestion was more in those with malignancy, while others like diffuse alveolar damage, microthrombi, pneumocyte hyperplasia, and so on, were equally distributed. In liver histopathology, architectural distortion was significantly different in immunocompromised; while steatosis, portal inflammation, Kupffer cell hypertrophy, and confluent necrosis were equally distributed. There was a trend towards higher acute tubular injury in those with cardiometabolic conditions as compared to the other groups. No significant histopathological difference in the heart was discerned. Certain histopathological features were markedly different in different groups (Gr 1, 2, and 3) of COVID-19 patients with fatal outcomes.